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Record W2563158171 · doi:10.1515/cclm-2016-0575

microRNAs in lipoprotein and lipid metabolism: from biological function to clinical application

2016· review· en· W2563158171 on OpenAlexaff
Véronique Desgagné, Luigi Bouchard, Renée Guérin

Bibliographic record

VenueClinical Chemistry and Laboratory Medicine (CCLM) · 2016
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-JeanUniversité de Sherbrooke
Fundersnot available
KeywordsmicroRNABiologyLipid metabolismContext (archaeology)RNATranslation (biology)BioinformaticsComputational biologyGeneMessenger RNAGeneticsEndocrinology

Abstract

fetched live from OpenAlex

microRNAs (miRNAs) are short (~22 nucleotides), non-coding, single-stranded RNA molecules that regulate the expression of target genes by partial sequence-specific base-pairing to the targeted mRNA 3'UTR, blocking its translation, and promoting its degradation or its sequestration into processing bodies. miRNAs are important regulators of several physiological processes including developmental and metabolic functions, but their concentration in circulation has also been reported to be altered in many pathological conditions such as familial hypercholesterolemia, cardiovascular diseases, obesity, type 2 diabetes, and cancers. In this review, we focus on the role of miRNAs in lipoprotein and lipid metabolism, with special attention to the well-characterized miR-33a/b, and on the huge potential of miRNAs for clinical application as biomarkers and therapeutics in the context of cardiometabolic diseases.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.376
Teacher spread0.329 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations54
Published2016
Admission routes1
Has abstractyes

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